scholarly journals Image Contrast Enhancement using Selfish Herd Optimizer

2020 ◽  
Author(s):  
Ritam Guha ◽  
Imran Alam ◽  
Suman Kumar Bera ◽  
Kushal Kanti Ghosh ◽  
Neeraj Kumar ◽  
...  
Keyword(s):  
Contrast Enhancement ◽  
Optimization Problem ◽  
Input Image ◽  
Image Contrast ◽  
Direct Approach ◽  
Pixel Intensity ◽  
Selfish Herd ◽  
Optimization Task ◽  
Image Contrast Enhancement ◽  
Ablation Study

Abstract Contrast enhancement is an important pre-processing task in any Image Analysis (IA) system. In this paper, we formulate the image contrast enhancement problem as an optimization problem where the goal is to optimize the pixel intensity values of an input image to obtain a contrast enhanced version of the same. This optimization task is executed by suitably customizing a nature-inspired optimization algorithm called Selfish Herd Optimizer (SHO). The optimization problem is solved using two different solution representations: pixel wise optimization (SHO(direct)) and transformation function based optimization (SHO(transformation)). Moreover, an ablation study is performed to select the most appropriate parameters which can be used in tness measure for this optimization problem. On experimenting over the popular Kodak image dataset, it has been observed that the proposed methods outperform many existing methods published recently. Further comparisons indicate that the direct approach performs better than its transformation counterpart. This paper further investigates the robustness of SHO(direct) approach by applying it to enhance the degraded document images of H-DIBCO 2018.

scholarly journals An Effective Image Contrast Enhancement Method Using Global Histogram Equalization

2010 ◽  
Vol 3 (1) ◽  
pp. 43 ◽  
Author(s):  
M. A. Yousuf ◽  
M. R. H. Rakib
Keyword(s):  
Contrast Enhancement ◽  
Image Enhancement ◽  
Histogram Equalization ◽  
Input Image ◽  
Image Contrast ◽  
Image Contrast Enhancement ◽  
Enhancement Method ◽  
Calculated Probability ◽  
The Mean ◽  
Processing Techniques

Image enhancement is one of the most important issues in low-level image processing. Histograms are the basis for numerous spatial domain processing techniques. In this paper, we present a simple and effective method for image contrast enhancement based on global histogram equalization. In this method, at first input image is normalized by making the minimum gray level value to 0.  Then the probability of each grey level is calculated from the available ROI grey levels. Finally, histogram equalization is performed on the input image based on the calculated probability density (or distribution) function. As a result, the mean brightness of the input image does not change significantly by the histogram equalization. Additionally, noise is prevented from being greatly amplified. Experimental results on medical images demonstrate that the proposed method can enhance the images effectively. The result is also compared with the result of image enhancement technique using local statistics.Keywords: Histogram equalization; Global histogram equalization; Image enhancement; Local statistics.© 2011 JSR Publications. ISSN: 2070-0237 (Print); 2070-0245 (Online). All rights reserved.doi:10.3329/jsr.v3i1.5299                J. Sci. Res. 3 (1), 43-50 (2011)

DCT Coefficients Weighting (DCTCW)-Based Gray Wolf Optimization (GWO) for Brightness Preserving Image Contrast Enhancement

2021 ◽  
Author(s):  
Saorabh Kumar Mondal ◽  
Arpitam Chatterjee ◽  
Bipan Tudu
Keyword(s):  
Contrast Enhancement ◽  
Objective Evaluation ◽  
Brightness Distribution ◽  
Image Contrast ◽  
Optimization Techniques ◽  
Biological Behavior ◽  
Gray Wolf ◽  
Original Image ◽  
Image Characteristics ◽  
Image Contrast Enhancement

Image contrast enhancement (CE) is a frequent image enhancement requirement in diverse applications. Histogram equalization (HE), in its conventional and different further improved ways, is a popular technique to enhance the image contrast. The conventional as well as many of the later versions of HE algorithms often cause loss of original image characteristics particularly brightness distribution of original image that results artificial appearance and feature loss in the enhanced image. Discrete Cosine Transform (DCT) coefficient mapping is one of the recent methods to minimize such problems while enhancing the image contrast. Tuning of DCT parameters plays a crucial role towards avoiding the saturations of pixel values. Optimization can be a possible solution to address this problem and generate contrast enhanced image preserving the desired original image characteristics. Biological behavior-inspired optimization techniques have shown remarkable betterment over conventional optimization techniques in different complex engineering problems. Gray wolf optimization (GWO) is a comparatively new algorithm in this domain that has shown promising potential. The objective function has been formulated using different parameters to retain original image characteristics. The objective evaluation against CEF, PCQI, FSIM, BRISQUE and NIQE with test images from three standard databases, namely, SIPI, TID and CSIQ shows that the presented method can result in values up to 1.4, 1.4, 0.94, 19 and 4.18, respectively, for the stated metrics which are competitive to the reported conventional and improved techniques. This paper can be considered a first-time application of GWO towards DCT-based image CE.

Ceed - A Database for Image Contrast Enhancement Evaluation

2018 ◽  
Author(s):  
Azeddine Beghdadi ◽  
Muhammad Ali Qureshi ◽  
Bilel Sdiri ◽  
Mohamed Deriche ◽  
Faouzi Alaya-Cheikh
Keyword(s):  
Contrast Enhancement ◽  
Image Contrast ◽  
Image Contrast Enhancement
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